Operation Ability Research Articles

Statistical Approach to Estimating Audience from MAC-Randomized WiFi Probe Requests.

In the past few years, the ability of wireless network operators to monitor audience using control frames emitted by client devices has been compromised, both by legislation treating client MAC addresses as private information and by the difficulty of distinguishing genuine client frames from those arising from the Internet of Things or from certain enhanced services. Here, a deterministic model, based on characteristics of human activity and on seasonal trends, is used to reveal underlying client statistics in raw MAC-randomized WiFi Probe Request data. The method proposes a candidate conversion factor, X, between probe request counts and the client population, which offers plausible predictions on real-world datasets.

Correlation between Chest Radiograph and Lung Ultrasound with Clinical Appearance in Hyaline Membrane Disease Patients

ABSTRACT Background: Hyaline membrane disease (HMD) is a respiratory distress disease in premature infants due to surfactant deficiency. The combination of clinical, laboratory and radiological features makes it easy to quickly, precisely & accurately establish HMD which is important for early therapy in preventing death. Purpose: Knowing the suitability between chest X-ray & Thorax ultrasound with the clinical picture in HMD patients. Methods: This study is an observational study with a cross sectional method conducted in the radiology & NICU section of Dr. Wahidin Sudirohusodo Makassar from August 2021 to January 2022. Sampling was done by consecutive sampling. The researcher performed a thorax ultrasound & assessed the chest x-ray. The results were verified by two pediatric radiology consultants. Results: The largest sample was in neonates at 34 weeks of gestation, 8 samples (21.1%), sex with 25 samples (65.8%), the highest birth weight between 1000-2000 grams 32 samples (84.2%) , the most preterm etiology was due to severe preeclampsia in 13 samples (34.2%), the most deliveries were by cesarean section 34 samples (89.4%), the highest APGAR Score was in moderate degree 25 samples (65.8%), the highest O2 saturation was between 90 -94%, namely 24 samples (63.2%), the most down scores were moderate degrees 15 samples (39.5%), HMD degrees based on chest radiographs were mostly grade II 25 samples (65.8%), HMD degrees based on thorax ultrasound the most in the moderate degree 19 samples (50%).Conclusion: Ultrasound is considered as the radiological modality of choice because it is safe, inexpensive, easy & sensitive to assess respiratory distress in neonates but is influenced by the operator's ability to apply it.Keywords: hyaline membrane disease, down score, chest radiograph, lung ultrasound

A near-infrared Fluorescent Probe Based on Dicyanisophorone for the Detection of Zinc Ions (Zn2+) in Water and Living Cells.

As one of the important metal ions, zinc ions (Zn2+) are widely involved in various physiological and pathological processes, and play fundamental roles in neurotransmission, cell metabolism and apoptosis. However, the convenient monitor of Zn2+ in environmental and biological samples remains challenging. In this study, a small molecule dicyanoisophorone-based schiff base incorporating with o-phenylenediamine was synthesized. It can rapidly combine with Zn2+ to emit significant near-infrared fluorescence (maximum emission wavelength: 660nm), so it can be used as a probe to quantitatively detect Zn2+ in the range of 0-10μM, with a detection limit as low as 4.8nM, showing the probe has high sensitivity for Zn2+. And the probe has a fast response time to Zn2+ (less than 30s) and a large Stoke-shift (179nm). In addition, the high recovery rates in practical water samples, and the clear fluorescent images in living A549 cells were obtained, which are of great significance for the detection of Zn2+ in the environment and biosystem. Due to its simple operation, good selectivity and anti-interference ability, short detection time and high sensitivity, this probe has great application potential as a fast detection tool for Zn2+ in environmental water and biological samples.

Online energy management strategy considering fuel cell fault for multi-stack fuel cell hybrid vehicle based on multi-agent reinforcement learning

Because of the high-power demand of fuel cell hybrid vehicles, a multi-stack fuel cell system (MFCS) composed of multiple low-power fuel cell stacks (FCSs) instead of a high-power one has become a satisfactory solution. This is due to the modularity of MFCS, which is more reliable and durable. However, the hybrid power system (MHPSS) of an MFCS hybrid electric vehicle possesses not only MFCS, but also batteries to improve the dynamic performance of MHPSS. Due to the difference in characteristics of MFCS and battery, the energy management strategy (EMS) of MHPSS is the key of ensuring its safe and efficient operation. However, most of the existing MHPSS EMSs are complicated in design and complex to compute online. Besides, they also do not consider the robustness of EMS, that is, EMS has the ability to guarantee the safe operation of MHPSS when the MFCS fails. To solve the above problems, this paper proposes an EMS based on independent Q-learning (IQL) which is an algorithm of multi-agent reinforcement learning to maintain battery state of charge (SOC) and minimize hydrogen consumption. The proposed EMS is not only simple in design, but also can guarantee the normal operation of the MHPSS when the MFCS fails, and can be transplanted to execute online on a microcontroller unit or a field programmable gate array. The various parts of the MHPSS model are first built, then the IQL strategy (IQLS) is trained offline in the established model environment, and finally, the IQLS is ported to the hardware-in-the-loop platform for validation. In order to verify the effectiveness of the proposed EMS, the solution of dimensionality-reduced DP is also used to calculate the fuel economy. Through the experimental verification under different initial SOC and driving cycles, it can be seen that the IQLS proposed in this paper can achieve the goal of maintaining battery SOC and minimizing hydrogen consumption, and also has good generalization ability and safe operation ability under fault conditions.

Rotor Loss and Temperature Field of Synchronous Condenser Under Single-Phase Short-Circuit Fault Affected by Different Materials of Rotor Slot Wedge

A synchronous condenser (SC) can provide the dynamic reactive power for the ultra-high-voltage direct current converter station during the system voltage drop caused by the single-phase short-circuit fault, which is one of the prevalent faults. However, the single-phase short-circuit fault can also result in the increase of the rotor loss and temperature and thus restrict the transient operating ability of the SC. A key factor that affects the rotor loss and temperature rise is the material of the rotor slot wedges. For a 300-MVar SC with the rotor slot wedges made of the aluminum, beryllium bronze, and stainless steel, the rotor loss and temperature distribution under the single-phase short-circuit are calculated by coupling the electromagnetic and temperature field models of the SC with the models of the power grid. The variations of the rotor losses along with the rotor slot wedge conductivity are revealed. The rotor regions, where the highest temperature rise appears, are obtained. According to the maximum permissible temperature of the rotor material, the transient operating ability of the SC withstanding the single-phase short-circuit fault is obtained. This article can provide the theoretic basis for improving the transient operating ability of the SC.

Influence of Rotor Slot Wedge Materials on Rotor Losses of Turbogenerator During Loss of Excitation

A short period of steady-state asynchronous operation after loss of excitation can improve the reliability of turbogenerator. The rotor damping structure of the turbogenerator can provide asynchronous torque and, thus, play an important role in improving the asynchronous operating ability. The rotor slot wedges as a part of rotor damping structure often made of aluminum, beryllium bronze, or stainless steel. The different materials of the rotor slot wedges can affect not only the asynchronous operating ability of the turbogenerator but also the rotor losses. The selection of material for the rotor slot wedges is therefore a key factor that should be carefully considered in the design of turbogenerator. In this article, the effect of the rotor slot wedges made of different materials on the asynchronous operating ability, rotor loss densities, and loss distributions of the turbogenerator after loss of excitation is investigated by time-stepping finite element model. The variations of the asynchronous operating ability and the rotor losses are revealed along with the rotor slot wedge conductivity. The rotor regions where the losses are significantly affected by the rotor slot wedge material are obtained. The results provide theoretic basis for improvement of the asynchronous operating ability and reduction of the rotor loss of turbogenerator.

How Analytics Is Facilitating Global Trade: Evidence from Modernizing the Global Supply Chain

Purpose – This analysis seeks to explore digitalization as a performance driver of supply chains, particularly the job of data analytics in the digitalization of procurement. The analysis investigates how electronic procurement abilities are connected to information analytics abilities and supply chain functional performance, and how this links to business results. Design/methodology/approach – Using dynamic and operational abilities as foundations for information analytics features, this study analyzed the electronic procurement abilities and proposed the conceptual style and hypotheses for empirical testing. The collected business survey information and structural equation strategy are then assessed to evaluate the hypotheses. Results – The study confirms favorable and significant associations between electronic procurement abilities, data analytics abilities and supply chain efficiency. Electronic procurement abilities mediate the good connection between external data analytics abilities and supply chain efficiency.Functional implications – From the managerial perspective, the findings highlight the benefits of increasing information from gathered information and digitalized procedures. Supervisors should look at information utilization abilities to improve the functionality expected from the digitalization of supply chain activities. Additionally, managers must think about exploiting information through new innovative methods as part of standardized activities. Originality/value – The current study plays a role in the present understanding by checking out the mediating role of data analytics features in between the digitalization of procurement and supply chain efficiency. The findings support a good connection between the data analytics abilities and supply chain performance in electronic upstream supply chain procurement procedures. The current study additionally clarifies the effect and role of data analytics features in electronic supply chain growth and achievement.

Development and control of an articulated mobile robot T2 snake-4.2 for plant disaster prevention – development of M2 arm and C-hand

ABSTRACT In this study, we develop an articulated mobile robot T Snake-4.2 that can move in narrow spaces, climb stairs, gather information, and operate valves for plant disaster prevention. We developed a novel folding arm M2 arm, fitted to the articulated mobile robot to have a better performance in mobility and operation ability compare to previous work T Snake-4. We introduce a novel method of climbing high steps and stairs by using the M2 arm as a support for the articulated mobile robot. T Snake-4.2 can climb high steps and stairs even with a heavy folding arm. In addition, we present a novel valve operating end effector, C-hand which allows the articulated mobile robot to open a large valve. By utilizing the shape characteristic of the valve, C-hand constraints to the environment and rotates the valve handle without transferring any reaction force to the robot and the folding arm. The developed robot T Snake-4.2 is tested through experiments in the laboratory and also in a field test at the Plant Disaster Prevention Challenge of World Robot Summit 2020.

A Study on Satisfaction and Willingness to Continuously Participate in Business Class Virtual Simulation Competitions -- An Empirical Analysis Based on Technology Acceptance Model (TAM)

The combination of virtual simulation technology and innovation and entrepreneurship education can achieve the role of interaction between the environment and the real environment during students’ virtual simulation, which can attract active participation of users and help college students understand the risks and opportunities faced by enterprises in the process of operation and growth, so as to improve the ability of enterprise operation and management, and deepen students’ understanding of theory and practical ability. In this paper, we construct a technology acceptance model (TAM) through seven dimensions: perceived usefulness, perceived ease of use, external environment, teacher guidance, willingness to participate, satisfaction, and willingness to continue to use, and investigate students’ satisfaction and willingness to continue to participate in the virtual simulation competition in some universities. The results of the data analysis show that the satisfaction and willingness to continue to participate in the virtual simulation competition play a good role.

Construction and Application of the Financial Early-Warning Model Based on the BP Neural Network.

In order to further improve the early-warning effect of enterprise financial crisis management and reduce the occurrence of enterprise financial crisis, by taking listed companies as examples and combining the operating conditions of listed companies, a financial crisis early-warning indicator system was built from five aspects of profitability, debt-paying ability, development ability, operation ability, and cash flow ability. In addition, a financial management early-warning model based on the BP neural network algorithm was built. Through the experimental prediction, it is showed that the financial crisis early-warning model of listed companies based on the BP neural network algorithm for crisis prediction accuracy was more than 75%. The accuracy of the first three years of model prediction was 93.33% and 72.34%, respectively. The accuracy of model prediction in the first two years was 94.67% and 82.98%, respectively. In the first year, the accuracy rate increased to 100% and 89.36%. Compared with the prediction accuracy of the logistic model (50%), it is fully reflected that the financial early-warning model proposed in the research had a good crisis prediction ability.

Using GPS Technology to Measure On-Time Running of Scheduled Bus Services

Assessing bus service running times has been a difficult and expensive task for many urban bus operators. This has restricted the ability of operators to collect adequate data to identify problems and improve service levels. Passive Global Positioning System (GPS) devices offer a low-cost means of collecting large amounts of highly accurate data, to be used in an ongoing performance assessment program. Some programming skills are required to break continuous GPS data into information that is meaningful to a scheduler. This article provides an overview of a software application developed to process and analyze GPS datasets collected by a bus operator in Sydney, Australia, in 2002-2003. The data collection procedure and processing algorithms are described, and examples are presented of output produced by the software. The algorithm developed to process the GPS data worked well. We conclude that passive GPS is a cost-effective method of collecting data on performance. For operators running buses on five or more routes, system development costs could be recovered within two to three years.

Service design of green and low-carbon intracity logistics: an AHP approach

ABSTRACT Climate change is the greatest global challenge faced by mankind today. With a rise in intelligent shared logistics and public awareness of environmental protection, implicit problems in intracity logistics, such as environmental pollution, resource waste, high carbon energy consumption and greenhouse gas emissions, should be solved urgently to achieve carbon neutrality. On this background, this study combines the analytic hierarchy process and gray correlation method to provide the best decision-making choice and benchmark enterprise for the green and low-carbon development of intracity logistics. In this research, the distribution business of six intracity logistics enterprises with the highest market share in China was investigated in detail. The target hierarchy standard focused on four aspects of green logistics: operation ability, infrastructure, resource utilisation and personnel factors. The four aspects are extended to 16 criteria. Supported by the survey data, this study provides a realistic reference for decision-making and a benchmark case for the low-carbon development of intracity logistics.

A Monolithic Optoelectronic Integrated Circuit of InP p-i-n/Double HBTs Through Transfer-Printing Fabrication

In this letter, we present a photoreceiver front-end circuit that consists of an InP p-i-n photodetector (PIN PD) on an InP transimpedance amplifier (TIA) with double HBTs (DHBTs), in which the key integrated fabrication route of a transfer-printing (TP) process is introduced. Prior to integration, PDs and TIAs are individually fabricated on their respective wafers. Then, a discrete PD with only active layers is transferred onto the destination on a TIA wafer, thereafter, an on-chip coplanar waveguide connection is integrated. The PIN PD and DHBT TIA exhibit excellent performance, characterized by a responsivity of 0.51 A/W at <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.55~\mu \text{m}$ </tex-math></inline-formula> with a bandwidth of 20 GHz and a transimpedance gain of 36 dB <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Omega $ </tex-math></inline-formula> with a bandwidth of 27 GHz, respectively. Finally, the monolithically integrated circuit demonstrates a better frequency response by maximally reducing the parasitic effect, with an open clear eye diagram under a 20 Gb/s nonreturn-to-zero pattern, which evidently manifests its ability for ultrahigh-rate data operation. The present work, by employing a TP process, overcomes the issues in integrating discrete optoelectronic devices and proposes a unique approach for monolithic optoelectronic integrated circuit fabrication.

Compact Vehicle Driver Fatigue Recognition Technology Based on EEG Signal

The driver’s fatigue directly affects the safety factor of the compact vehicle driving in actual road. Mastering the driver’s fatigue state plays an important role in the driver’s safety driving and timely adjustment of mental state. In view of the particularity of the driving safety of the compact vehicle, this paper takes the driver’s brain electricity (EEG) signal as the research object, and starts from the formulation of the experimental scheme, and based on the special training system in the simulation driving software. Two types of driving quality evaluation indicators: the fine operation ability and emergency response capability is formulated; after preprocessing and eigenvalue selection of EEG signals, DPCA clustering algorithm combined with driving quality is used to complete the classification of driver fatigue and the marking of EEG signal feature data set. Finally, the driver fatigue recognition model is initially constructed by using the labeled data set combined with the convolutional neural network (CNN).

Best-practice recommendations for cautery disbudding goat kids

Abstract Cautery disbudding is a painful husbandry practice routinely performed on goat kids using a hot cautery iron to destroy the horn buds and prevent horn growth. After a thorough review of the scientific literature on cautery disbudding of goat kids, it is apparent that there is considerable variation in disbudding practice in relation to training, kid-related factors (e.g. age, sex), iron-related factors (e.g. temperature, application time), procedure (e.g. horn bud removal), and pain mitigation, which all can impact the behaviour and welfare of goat kids. This case study provides best-practice recommendations for cautery disbudding goat kids. It is imperative that goat kid-specific training, with allowance for time and opportunities for practice, is provided to improve the technical ability of operators, and to reduce the potential for negative impacts on kid health and welfare. Procedural factors to be taken into consideration in preparation for disbudding include age of goat kid at disbudding, sex, temperature and application time of the iron, and whether the horn bud is removed. Goat kids typically are very vocal with rapid and intense movements during disbudding, and they perform head shaking and scratching following disbudding, which can be alleviated with appropriate pain management. Isoflurane or dexmedetomidine and non-steroidal anti-inflammatory drugs such as meloxicam can reduce pain, whereas lidocaine blocks have varying efficacy and cause pain to administer. Goat kid-focused best-practice recommendations for cautery disbudding can improve the health and welfare outcomes for goat kids.

Efficient and low-cost solar desalination device with enhanced condensation on nail arrays

Portable solar desalination is attracting increasing attention in recent years, due to its off-grid operating ability. Despite considerable progresses in solar evaporation, the inefficient condensation in air and exorbitant water production cost strongly limit the real applications. Here, we propose a solar desalination device with cheap brass nail arrays as effective condenser. With reduced evaporator-to-nail distance, vapor flux concentration at nail tip and vertically aligned surface of nail body, the vapor diffusion, condensation and condensate shedding can be enhanced simultaneously. Guided by a comprehensive modeling of the vapor transport, an optimized device was fabricated and tested. A solar-to-water efficiency of 51.13 % was demonstrated with nail array condenser, which was 10.24 % higher than that with conventional plate condenser. In addition, all the selected materials are cheap and durable. Due to the high energy efficiency and low cost, this design is promising to relieve the water shortage in off-grid regions.

Determination of Production Targets on Sewing for the Front Body of H&amp;M Pajamas Jogger Pants

The process of sewing the front body of an order for H&amp;M Pajamas Jogger Pants has a fairly high quality, but the target for setting production targets is based on experience and estimates only. The setting of a fairly high production target of 640 pcs/day is often not achieved because the determination of the production target is not based on the level of difficulty of the work carried out by the operator (easy, medium, or difficult), the operator's skill as well as the condition of the machine used in the process. condition is good or not, so that the target set is often not achieved because it is not in accordance with the condition of the operator's ability in general. Based on the observation of the operator's working time measurement, the total standard time for the 26 manufacturing processes for the front body component of the order of H&amp;M Pajamas Jogger Pants was 23,029 minutes. After getting the total standard time for making the front body component of the order for these H&amp;M Pajamas Jogger Pants, a new production target can be determined, which is 542 pcs/day. This new production target is made to represent the general working conditions of operators and has taken into account the factors of slack, work fatigue and other unavoidable obstacles.

Research on Embedded Ball Screw Diagnosis System for Mechanical Fault Based on Bispectral Image

Ball screw is one of the main basic transmission components in CNC machine tool feed system because of its high transmission efficiency, positioning accuracy, and rigidity. It plays an irreplaceable role in the process of machine tool torque transmission and positioning. However, ball screw is also one of the parts which are easy to break down in the feed system. If it breaks down, it will affect the processing accuracy of the whole machine tool and even cause shutdown. Numerical control means that digital control is a high-efficiency technology that uses digital information to control mechanical movement and processing processes. Therefore, to increase the high-speed and high-precision operation ability of CNC machine tools, research and development of efficient and reliable predictive maintenance and issue identification technology to guide maintenance of CNC machine tools are critical. Throughout this study, a bispectrum image-based embedded defect fight against the disease for cylindrical gears is provided. Firstly, the bispectrum of fault signal is generated by Wavelet Packet Threshold denoising, wavelet packet reconstruction, and bispectrum analysis, and the characteristics of bispectrum are represented by the first kind of gray moments. These feature statistics are used as input feature vectors of BP neural network pattern recognition algorithm to classify these feature sets and identify the corresponding gear fault types. Experiments show that under the condition of noise, after 14.5 hours of testing, the NGI has increased significantly and can be used to diagnose faults in the gear system, and the method achieves relatively ideal recognition rate and verifies the feasibility of gear box fault diagnosis method based on image recognition. The code compiled by OpenCV library is easy to transplant to embedded system, with high development efficiency and reliable program operation. OpenCV has the characteristics of powerful matrix computing capability and convenient and flexible interface, and it is a general algorithm that can realize real-time image processing.

Design of the Artificial Intelligence Vocal System for Music Education by Using Speech Recognition Simulation.

At present, computer technology is not limited to the network but to many aspects of spread out, including artificial intelligence technology, signal processing technology, speech recognition technology, and so on which have been better developed, and music teaching has also obtained certain achievements. If the detected speech data have no other clutter in the speech, then the endpoint detection can achieve ideal results. The music education system includes the development of four dimensions: WEB terminal, mobile terminal, web interface, and database. Using the powerful functions of computers, such as computing functions and processing functions, combined with advanced intelligent technology and related equipment, the intelligent learning model based on computer technology is established. It can be applied in college teaching, combined with the actual needs of current college music teaching, corresponding to the curriculum and teaching plan issued by the school, combined with the design of online learning system and reasonable use of computer technology to build a vocal music education system. The intelligent system can improve the requirements of vocal music education management level, teaching organization ability, and teaching platform operation ability.

Comparative evaluation of the pump mode and turbine mode performance of a large vaned-voluted centrifugal pump

Large vaned-voluted centrifugal pump is a general machine used for large-scale water diversion. As a vane-type hydraulic machinery, it also has the ability of reversible operation. With the introduction of policies to reduce carbon emissions, the proportion of unstable new energy use has increased. The existing large centrifugal pump unit can realize the function of reverse power transfer. For peak shaving and valley filling of power grid, it has high feasibility and economy. In this paper, a large vaned-voluted centrifugal pump is simulated numerically, it is external characteristics and flow state under positive and negative rotation are obtained, its performance is predicted by best efficiency point method, and it is found that pump reversal can run at the optimum efficiency point with higher flow rate and head. Error analysis is carried out for different formulas. The flow energy dissipation (FED) of different flow rates under positive and negative rotation is analyzed. It is found that the main energy loss locates on suction side of blade, inlet and outlet part of blade and tail part of guide blade head. By comparing the flow energy dissipation distribution under the same flow conditions with positive and reverse rotation, it is found that the high energy loss area of blade mainly exists in inlet and outlet part of blade in pump mode. The high energy loss area of the blades in turbine mode mainly exists in the inlet part of the blades. This study is of great significance to the operation of low-carbon power grid assisted by existing reservoirs and hydraulic machinery.